Metrics to quantify the importance of mixing state for CCN activity
It is commonly assumed that models are more prone to errors in predicted cloud condensation nuclei (CCN) concentrations when the aerosol populations are externally mixed. In this work we investigate this assumption by using the mixing state index (<i>χ</i>) proposed by Riemer and West...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-06-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | http://www.atmos-chem-phys.net/17/7445/2017/acp-17-7445-2017.pdf |
| Summary: | It is commonly assumed that models are more prone to errors in predicted
cloud condensation nuclei (CCN) concentrations when the aerosol populations
are externally mixed. In this work we investigate this assumption by using
the mixing state index (<i>χ</i>) proposed by Riemer and West (2013) to quantify
the degree of external and internal mixing of aerosol populations. We combine
this metric with particle-resolved model simulations to quantify error in CCN
predictions when mixing state information is neglected, exploring a range of
scenarios that cover different conditions of aerosol aging. We show that
mixing state information does indeed become unimportant for more internally
mixed populations, more precisely for populations with <i>χ</i> larger than
75 %. For more externally mixed populations (<i>χ</i> below 20 %) the
relationship of <i>χ</i> and the error in CCN predictions is not unique and
ranges from lower than −40 % to about 150 %, depending on the
underlying aerosol population and the environmental supersaturation. We
explain the reasons for this behavior with detailed process analyses. |
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| ISSN: | 1680-7316 1680-7324 |